# Plot method for the regress function

### Description

Plot method for the regress function

### Usage

1 2 3 |

### Arguments

`x` |
Return value from |

`plots` |
Regression plots to produce for the specified regression model. Enter "" to avoid showing any plots (default). "hist" to show histograms of all variables in the model. "correlations" for a visual representation of the correlation matrix selected variables. "scatter" to show scatter plots (or box plots for factors) for the response variable with each explanatory variable. "dashboard" for a series of six plots that can be used to evaluate model fit visually. "resid_pred" to plot the explanatory variables against the model residuals. "coef" for a coefficient plot with adjustable confidence intervals. "leverage" to show leverage plots for each explanatory variable |

`lines` |
Optional lines to include in the select plot. "line" to include a line through a scatter plot. "loess" to include a polynomial regression fit line. To include both use c("line","loess") |

`conf_lev` |
Confidence level used to estimate confidence intervals (.95 is the default) |

`intercept` |
Include the intercept in the coefficient plot (TRUE, FALSE). FALSE is the default |

`shiny` |
Did the function call originate inside a shiny app |

`custom` |
Logical (TRUE, FALSE) to indicate if ggplot object (or list of ggplot objects) should be returned. This opion can be used to customize plots (e.g., add a title, change x and y labels, etc.). See examples and http://docs.ggplot2.org/ for options. |

`...` |
further arguments passed to or from other methods |

### Details

See http://radiant-rstats.github.io/docs/model/regress.html for an example in Radiant

### See Also

`regress`

to generate the results

`summary.regress`

to summarize results

`predict.regress`

to generate predictions

### Examples

1 2 3 4 5 6 7 | ```
result <- regress("diamonds", "price", c("carat","clarity"))
plot(result, plots = "dashboard", lines = c("line","loess"))
plot(result, plots = "coef", conf_lev = .99, intercept = TRUE)
plot(result, plots = "hist")
plot(result, plots = "scatter", lines = c("line","loess"))
plot(result, plots = "correlations")
plot(result, plots = "resid_pred", lines = "line")
``` |